作品名称: 盗まれた人妻 作者: #平つくね 作者简介: 日本漫画家、插画师,社团 ROUTE1。商业向画过《ラッキー・ブレイク》,也给《エクスタス・オンライン》做人物原案,同人侧常画人妻和关系错位 内容介绍:已婚女人被别的男人盯上,一步步从家里被带走。丈夫还蒙在鼓里,她已经回不去原来的位置。所有角色按成年设定。 图翻不动就滑到最底下用 PDF,是飞机的问题。 风格标签: #盗まれた人妻 #平つくね #本子 #人妻 #成人
👍3❤2🤡2💯1🤯1

Channel
@manhuashaonv
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Handles named that no longer answer · Cite this entry
103,516subscribers
+998 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
| Telegram ID | -1002009965836 |
|---|---|
| Type | Channel |
| Username | @manhuashaonv |
| Created | Between 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 30 September 2026 |
| Measurements held | 34 |
| Confirmed unchanged | 1 time, most recently 30 September 2026 |
| On Telegram | t.me/manhuashaonv |
Adult — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 30 Sept 2026, 11:59 | 103,516 | +766 |
| 18 Sept 2026, 01:38 | 102,750 | +578 |
| 15 Sept 2026, 20:16 | 102,172 | +782 |
| 14 Sept 2026, 04:01 | 101,390 | +80 |
| 12 Sept 2026, 10:37 | 101,310 | -18 |
| 10 Sept 2026, 06:38 | 101,328 | +28 |
| 7 Sept 2026, 03:59 | 101,300 | +16 |
| 4 Sept 2026, 09:15 | 101,284 | +23 |
| 2 Sept 2026, 23:18 | 101,261 | -12 |
| 1 Sept 2026, 19:47 | 101,273 | -24 |
| 31 Aug 2026, 22:17 | 101,297 | -22 |
| 30 Aug 2026, 03:05 | 101,319 | -17 |
| 29 Aug 2026, 00:04 | 101,336 | -48 |
| 27 Aug 2026, 23:25 | 101,384 | -42 |
| 26 Aug 2026, 22:13 | 101,426 | -40 |
| 25 Aug 2026, 21:48 | 101,466 | -49 |
| 24 Aug 2026, 21:43 | 101,515 | -45 |
| 23 Aug 2026, 07:54 | 101,560 | -89 |
| 21 Aug 2026, 18:58 | 101,649 | -30 |
| 20 Aug 2026, 19:23 | 101,679 | first reading |
224 posts held, back to 1 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 112 pages of Telegram’s post history, 20 posts per page.
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 107 of 116 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 29 September 2026 |
|---|---|
| Posts held | 224 (1 August 2026 – 29 September 2026) |
| Views total | 313,739 |
| Reactions total | 910 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 30 Sept 2026, 11:22 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
Measured directly from 98 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
1,476 reactions across 207 posts, in 20 distinct kinds. The most used accounts for 30.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 455 | 30.8% | |
| 🤡 | 351 | 23.8% | |
| 👍 | 345 | 23.4% | |
| 💯 | 147 | 9.96% | |
| 🔥 | 96 | 6.50% | |
| 🤯 | 49 | 3.32% | |
| 🥴 | 9 | 0.61% | |
| 👏 | 7 | 0.474% | |
| 😢 | 3 | 0.203% | |
| 🎉 | 2 | 0.136% | |
| 🕊 | 2 | 0.136% | |
| 😁 | 2 | 0.136% | |
| ❤🔥 | 1 | 0.068% | |
| 👀 | 1 | 0.068% | |
| 😍 | 1 | 0.068% | |
| 😭 | 1 | 0.068% | |
| 😴 | 1 | 0.068% | |
| 🤬 | 1 | 0.068% | |
| 🤮 | 1 | 0.068% | |
| 🥰 | 1 | 0.068% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 207 of the 224 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 1,476 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 224 most recent posts we hold, published 1 August 2026 to 29 September 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @manhuashaonv. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 224 most recent posts we hold for this entry, published 1 August 2026 to 29 September 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
作品名称: 盗まれた人妻 作者: #平つくね 作者简介: 日本漫画家、插画师,社团 ROUTE1。商业向画过《ラッキー・ブレイク》,也给《エクスタス・オンライン》做人物原案,同人侧常画人妻和关系错位 内容介绍:已婚女人被别的男人盯上,一步步从家里被带走。丈夫还蒙在鼓里,她已经回不去原来的位置。所有角色按成年设定。 图翻不动就滑到最底下用 PDF,是飞机的问题。 风格标签: #盗まれた人妻 #平つくね #本子 #人妻 #成人
👍3❤2🤡2💯1🤯1
想喝奈奈..... 😀
👍3🔥2🤡2💯1
作品名称: ゆかりん【完全版】_20260911🆕 作者: #梅澤一手 内容介绍:9月作品,日期2026年9月11日。主角是ゆかりん,这一支是完全版,把之前没放全的部分补上了。人还是同一个人,篇幅更完整。所有角色按成年设定。 风格标签:#梅澤一手 #ゆかりん #完全版 #9月作品 #成人向
👍3🤡2❤1💯1🤯1
作品名称: お祈り中の勃起事故♡(前編)2026年9月23日作品🆕 作者: #cameel 作者简介: 专画正经场面突然翻车,表情细,气氛拉得住。 内容介绍:女孩低头祈祷,手还合着。对方没等她做完,一步步靠近,她嘴里的词直接断掉。本该安静的祈祷,最后变成两个人在原地把事做完。所有角色按成年设定。 风格标签: #cameel #fantia #同人 #成人向
👍3❤2🤡2🔥1🤯1
作品名称: 夏妻3 作者:#黒巣ガタリ 作者简介: 画已婚女性出轨题材,表情和关系写得比较细。 内容介绍:已婚女人在外面和别的男人发生关系,回家还要装着没事。这一作接着写她怎么瞒、怎么被拉得更远。所有角色按成年设定。 图翻不动就滑到最底下用 PDF,是飞机的问题。 风格标签: #夏妻3 #黒巣ガタリ #本子 #熟女 #成人向
👍2🤡2❤1🔥1🤯1
作品名称:《とろかせおるがずむ》(美魔女的究极高潮) 作者:#おるとろ 作者简介:擅长描绘成熟女性细腻情绪与自然互动的漫画家,画风柔和流畅,注重角色表情与氛围表现。 内容介绍:以一位成熟美丽的女性为主角,展开一段轻松自然的私密互动故事。内容强调细腻的情绪变化与舒适的相处氛围,带来沉浸式阅读体验。所有角色均按成年设定。 风格标签:#美魔女的究极高潮 #单行本 #漫画 #成人向
❤3👍2💯2🤡2🤯1
作品名称:《崩坏三 瑟莉姆 私密互动》 作者:#HimuraMegumin 作者简介:专注游戏角色同人创作的成人向画师,擅长细腻刻画角色情绪与自然互动,作品风格流畅真实。 内容介绍:以崩坏三角色瑟莉姆为主角,展开一段轻松自然的私密互动故事。内容强调角色间的细腻交流与舒适氛围,带来沉浸式观看体验。所有角色均按成年设定。 风格标签:#崩坏三 #同人 #火车便当 #HimuraMegumin #260914d
👍3❤2🤡2🔥1🤯1
作品名称:《爆炒梨诺》26.9新作🆕 作者:#LunaElle 作者简介:专注真实互动风格的成人向创作者,擅长捕捉自然情绪与细腻肢体交流,作品节奏流畅、画面真实。 内容介绍:以轻松自然的节奏展开一段深入的私密互动。内容强调真实的情绪变化与舒适的相处氛围,带来沉浸式观看体验。所有参与者均按成年设定。 风格标签:#真实互动 #私密时光 #流畅节奏 #成人向
👍3🤡2❤1💯1🤯1
作品名称:《知らない女性から画像共有でエロい自撮りが送られてきた話》 作者:#犬上いの字 作者简介:擅长描绘成熟女性日常与细腻互动的漫画家,画风干净细腻,注重角色表情与氛围营造。 内容介绍:一位陌生女性通过图片分享功能陆续发来自拍。故事围绕这些意外收到的照片展开,描绘成熟女性戴着眼镜、穿着连裤袜的日常瞬间与细微情绪变化,带来轻松舒适的阅读体验。所有角色均按成年设定。 风格标签:#眼镜 #熟女 #连裤袜 #日常向 #成人向漫画
👍2🤡2❤1💯1🤯1
作品名称:《一直不停對熟女叔母說可愛的外甥》 作者:#藤崎チロ 作者简介:擅长描绘成熟女性与日常互动题材的漫画家,画风细腻全彩,注重角色表情与氛围营造,善于表现轻松又带有温度的情感交流。 内容介绍:一位戴着眼镜的成熟叔母,与总是不停夸她可爱的外甥之间,展开一段自然又微妙的日常互动。作品以全彩细腻的笔触刻画两人相处的温馨氛围与细微情绪变化,带来舒适的阅读体验。所有角色均按成年设定。 风格标签:#熟女 #全彩 #眼镜 #日常互动 #温馨向 #成人向漫画
❤5👍3💯2🔥1🤡1
作品名称:《同人作品》26年9月🆕 作者:#laomeng 作者简介:专注同人创作的漫画家,擅长细腻情感与自然互动表现,画风清新流畅,注重角色之间的默契与日常氛围营造。 内容介绍:以轻松自然的节奏展开一段同人向互动故事。画面强调角色间的细腻交流与舒适氛围,带来愉悦的阅读体验。所有角色均按成年设定。 风格标签:#同人 #轻松日常 #细腻互动 #清新画风 #成人向漫画
❤4👍2💯1🤡1
作品名称:《德福·纵享丝滑》26年9月新作🆕 作者:#apoluna 作者简介:擅长细腻情感与流畅画面表现的创作者,作品注重角色互动的自然节奏与视觉舒适感,风格清新顺滑,适合喜欢轻松氛围的读者。 内容介绍:以轻松流畅的节奏展开一段细腻互动故事。画面强调丝滑的肢体表现与舒适的情感交流,带来自然而愉悦的阅读体验。所有角色均按成年设定。 风格标签:#轻松日常 #细腻互动 #流畅画风 #舒适向 #成人向漫画
❤2👍1💯1🔥1🤡1
Showing the 12 most recent of 224 posts we hold for @manhuashaonv. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
@manhuashaonv named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 30 September 2026 — this entry's latest reading, not the date you are reading this.
“二次元|漫画里番【NSFW】” (@manhuashaonv), 103,516 subscribers as measured 30 September 2026. Telegram Register, tgregister.com/channel/manhuashaonv.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.